hsliu
154d9ca4ff
- Add complete directory structure for multimodal and non-autoregressive processing - Include AsyncLLM, OmniEngine, and DiffusionEngine modules - Add processors, schedulers, executors, and output processors - Add API interfaces for Higress, Gradio, and ComfyUI - Add configuration management and CLI interface - Add comprehensive test structure and documentation - Add pyproject.toml with dependencies and project configuration - Add examples and documentation structure
119 lines
3.0 KiB
Python
119 lines
3.0 KiB
Python
"""
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Pytest configuration and fixtures for vLLM-omni tests.
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"""
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import pytest
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import asyncio
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from typing import AsyncGenerator, Generator
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from unittest.mock import Mock, AsyncMock
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import torch
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import numpy as np
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from vllm_omni.configs import load_config
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@pytest.fixture(scope="session")
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def event_loop() -> Generator[asyncio.AbstractEventLoop, None, None]:
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"""Create an instance of the default event loop for the test session."""
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loop = asyncio.get_event_loop_policy().new_event_loop()
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yield loop
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loop.close()
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@pytest.fixture
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async def mock_async_llm() -> AsyncMock:
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"""Mock AsyncLLM for testing."""
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mock = AsyncMock()
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mock.process.return_value = {"output": "test_output", "hidden_states": None}
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return mock
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@pytest.fixture
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async def mock_omni_engine() -> AsyncMock:
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"""Mock OmniEngine for testing."""
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mock = AsyncMock()
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mock.execute.return_value = {"result": "test_result"}
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return mock
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@pytest.fixture
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def sample_config() -> dict:
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"""Sample configuration for testing."""
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return {
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"general": {
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"name": "vllm-omni-test",
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"version": "0.1.0",
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"debug": True,
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"log_level": "DEBUG"
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},
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"model": {
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"device": "cpu",
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"dtype": "float32",
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"max_model_len": 1024
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},
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"engines": {
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"ar_engine": {"enabled": True, "max_batch_size": 32},
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"diffusion_engine": {"enabled": True, "max_batch_size": 8}
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}
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}
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@pytest.fixture
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def sample_text_input() -> str:
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"""Sample text input for testing."""
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return "Hello, world! This is a test input for vLLM-omni."
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@pytest.fixture
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def sample_image_input() -> np.ndarray:
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"""Sample image input for testing."""
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return np.random.randint(0, 255, (224, 224, 3), dtype=np.uint8)
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@pytest.fixture
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def sample_audio_input() -> np.ndarray:
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"""Sample audio input for testing."""
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return np.random.randn(16000).astype(np.float32) # 1 second at 16kHz
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@pytest.fixture
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def sample_multimodal_input() -> dict:
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"""Sample multimodal input for testing."""
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return {
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"text": "Describe this image",
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"image": np.random.randint(0, 255, (224, 224, 3), dtype=np.uint8),
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"audio": np.random.randn(16000).astype(np.float32)
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}
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@pytest.fixture
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def mock_torch_device() -> str:
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"""Mock torch device for testing."""
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if torch.cuda.is_available():
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return "cuda"
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elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
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return "mps"
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else:
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return "cpu"
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# Pytest markers
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pytest_plugins = []
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def pytest_configure(config):
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"""Configure pytest with custom markers."""
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config.addinivalue_line(
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"markers", "unit: mark test as a unit test"
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)
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config.addinivalue_line(
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"markers", "integration: mark test as an integration test"
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)
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config.addinivalue_line(
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"markers", "benchmark: mark test as a benchmark test"
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)
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config.addinivalue_line(
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"markers", "slow: mark test as slow running"
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)
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